Research On The Influence Of Online Evaluation Cumulative Effect On The Deal Volume Of Shared Economic Platform

As a new business model,the sharing economy takes the temporary transfer of usage right through public network platforms as the essence.It takes the repeated transaction and efficient use of the goods as the manifestation form,and socialized use the idle resources owned by individuals.The current sharing economy is growing rapidly.But the sharing economic development of China is facing two outstanding issues.The first is the dishonest and uncivilized behavior of the platform participants,which involves the sharing economy's credit evaluation mechanism.The second is to share predatory pricing strategies b etween platforms.In particular,the so-called "burn wars" that provide subsidies to users at the initial stage of the establishment of the platform.Is there a connection between the two? This article introduces the cumulative effect of online evaluation,take Airbnb as an example provide a generalized theoretical explanation for the above phenomenon.In the second part of this paper,analyze the Airbnb platform credit evaluation mechanism firstly.Then established the game matrix of the platform,the landlord and the tenant,and the game equilibrium state is deduced in consideration of the platform to participate in the deletion of bad reviews and platform participation can delete bad reviews.Discuss the impact of cumulative evaluation on landlords and p latforms and creative cumulative effect.It was found that increasing the cumulative evaluation volume can reduce the landlord's transaction costs and improve the landlord's ability to respond to bad evaluations.While maintaining their own interests,increasing the number of potential tenants in the future will have a positive impact on future trading volume.Expanded to the platform,the increase in cumulative volume represents a large number of users on the platform,and the network traffic is large enough to attract more potential users.Finally,the analysis of the game model is extended to the industrial organization level.From the perspective of market structure,the more significant the cumulative effect,the higher the degree of industrial concentration.From the perspective of corporate behavior,the more significant the cumulative effect,the more companies tend to evict competitors at lower prices,creating a burning money battle between platforms.In the third part of this paper,quantile regression is used to make a comparative analysis on the influence of online evaluation on the deal volume of Airbnb of C hina and US.Captured the data of the Airbnb p latform in the Shanghai and New York and data statistics,the data source for the Airbnb website.The empirical test of the impact of evaluation on the trading volume of the platform use cumulative evaluations and scores as the main explanatory variables.With comparing the Sino-U.S.regional variable coefficients changes in different locator points,this paper discuss the effect of explanatory variables on the explanatory variables.Found that for cumulative evaluation,the trend of the coefficient rising first ly and then decreasing shows that with the trading volume increases,the impact of cumulative evaluation on the decision-making of tenants appears to rise first and then decrease.The empirical results also verify that the trading volume of the Airbnb platform in C hina and the United States is not affected by the cumulative evaluation amount,which is mainly due to the difference in the credit environment between the two countries.Finally,based on the conclusions,this paper puts forward the policy suggestions of this paper,which are divided into two parts: the shared economic platform and government departments.